Kafka Streams with Spring Cloud Stream

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2023-01-15
Learners

No Information
Duration

No Information
Instructor

Learning JournalPrashant Kumar Pandey

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4.2

4,152 Ratings

Learn Kafka Streams with Spring Cloud Stream and gain a deep understanding of stream processing. This course takes a progressive common-sense approach to teaching a complex subject, allowing you to perceive, understand, and reason the concepts progressively. Designed for software engineers, data architects, and data engineers, this course will help you develop stream processing applications using the Kafka Streams library and Spring Boot. With fully example-driven lessons, you'll have the opportunity to practice and apply your knowledge using industry-standard tools like IntelliJ IDEA, Apache Maven, and JUnit5. Don't miss out on this opportunity to enhance your skills and solve real-world programming problems.

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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [September 05th, 2023]

Skills and Knowledge Acquisition:
Participants in the "Kafka Streams with Spring Cloud Stream" course will acquire the following skills and knowledge:

Stream Processing Fundamentals: Gain a strong foundation in stream processing concepts and understand how Kafka Streams fits into the larger stream processing landscape.

Kafka Streams Programming: Learn how to program with Kafka Streams, using Spring Boot as the framework to build real-time stream processing applications.

Application Development: Develop practical skills in designing and building stream processing applications using Kafka Streams and Spring Cloud Stream.

Compatibility and Versioning: Understand how to work with Kafka Streams libraries compatible with Spring Cloud 2020 and Apache Kafka 2.6, ensuring the ability to work with different versions of Kafka.

Development Tools: Familiarize yourself with development tools such as IntelliJ IDEA, Apache Maven, Gradle, and Log4J2, as they are used in the course to develop and manage Kafka Streams applications.

Unit Testing: Learn to implement unit test cases using JUnit5, enabling the creation of robust and reliable stream processing applications.

Practical Examples and Exercises: Apply your knowledge through numerous practical examples and exercises provided in the course, which help transform theoretical understanding into practical skills.

Contribution to Professional Growth:
This course offers significant contributions to professional growth:

Stream Processing Proficiency: Mastering Kafka Streams and Spring Cloud Stream empowers software engineers, data architects, and data engineers to excel in developing stream processing applications, which are increasingly in demand in various industries.

Versatility and Expertise: Acquiring skills in stream processing enhances one's versatility and expertise, making them valuable assets in organizations adopting real-time data processing solutions.

Problem-Solving Skills: Practical exercises and examples offered in the course strengthen participants' problem-solving abilities in the context of stream processing and Kafka Streams.

Suitability for Preparing Further Education:
The "Kafka Streams with Spring Cloud Stream" course is suitable for individuals preparing for further education or seeking to deepen their knowledge in the field of stream processing and Kafka Streams:

Graduate Studies: Students pursuing advanced degrees in data engineering, computer science, or related fields can use this course as a foundation for deeper exploration of stream processing technologies.

Certification: Those planning to pursue certifications related to Kafka Streams or real-time data processing can benefit from this course as a preparation resource.

Professional Development: IT professionals looking to expand their knowledge of stream processing and Kafka Streams can use this course to enhance their expertise and prepare for further career advancement.

Course Syllabus

Before you begin

Environment setup on Windows Machine

Environment Setup on Mac Machine

Understanding the technology stack

Producing Data to Kafka

Processing Kafka Streams

Working with KStream

KTable and Aggregations

Timestamp and Windowing Aggregates

Joins in Kafka Streams

Kafka Streams in Functional Style and Unit Testing

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